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Li L.,Sun Yat Sen University | Li L.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | Li J.,Sun Yat Sen University | Li J.,Guangdong Provincial Key Laboratory of Intelligent Transportation System
Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of Technology | Year: 2011

The generalized transit travel time is proposed in consideration of number of transfers, travel time, travel distance, walking distance, waiting time, etc; and the utility function of different transits are constructed according to the generalized transit travel time and travel cost. The nested-logit choice model is proposed to separate the modal choice and route choice. The case study of Guangzhou City is presented whose model parameters are obtained though questionnaire survey. A comparison between model results and survey data shows that the proposed model produces feasible and reliable results. Source


Niu Z.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | Niu Z.,Sun Yat Sen University | Huang M.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | Huang M.,Sun Yat Sen University | And 2 more authors.
Xitong Fangzhen Xuebao / Journal of System Simulation | Year: 2016

In order to realize the intelligent management of road guide signs, a method of visualization of road guide sign panel based on the flexible combination of guiding information was proposed. As a consequence of analysis for structures of guide sign panel, the message on the guide sign panel was decomposed into guiding information, and then visualization function was proposed. The panel style was determined by the physical and logical topology of guiding intersection dynamically with the help of guide sign system database. Then the composition of geography information and guiding information was utilized in the process of visualization. The visualization method was tested in the Guangzhou Higher Education Mega Center, and the visual panels created by the method shared the most widely features with guide panels in reality. The result reveals that the algorithm is feasible and effective. © 2016, The Editorial Board of Journal of System Simulation. All right reserved. Source


Li F.-W.,Sun Yat Sen University | Li F.-W.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | Li F.-W.,Application Security | Li X.-Y.,Sun Yat Sen University | And 5 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013

The radiator grille is an important feature to distinguish the style of vehicle, and also helpful to the automatic recognition of vehicle type. The radiator grille image which is split from the vehicle face is treated as a texture image. By analyzing the Fourier spectrum of the radiator grille image, visual features are extracted. According to the visual features, radiator grilles are classified into different sorts, such as longitudinal or transverse. Compared with other feature extraction methods, the test result shows that the proposed method is effective for the accuracy reaches more than 80%. © 2013 SPIE. Source


Hu J.-H.,Sun Yat Sen University | Hu J.-H.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | Deng J.,Sun Yat Sen University | Deng J.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | And 2 more authors.
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | Year: 2014

This paper summarizes the research status of identifying the alighting stations of smart card passengers for flat-rate fare lines. To make best use of passenger trip chains and passenger flow of stations, it analyzes transit travel characteristics and proposes a number of assumptions. Based on these assumptions, it defines relative variables to describe passenger trip chains and considers individual characteristics for alighting attraction weighting. Then, the paper combines disaggregate analysis and aggregate analysis according to the completeness of passenger trip chains and then formulates the bus passenger alighting weight model. It also proposes the algorithm to solve the established model and a calibration method of the model. Finally, it takes Line 448 in Guangzhou city as an example and compared the identifying results of this new model with the identifying results of the disaggregate analysis model. The results show that the new model is more applicative in identifying the alighting stations of smart card passengers and has high reliability in a cluster analysis. Source


Xing H.,Sun Yat Sen University | Xing H.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | Xu W.,Guangdong Provincial Key Laboratory of Intelligent Transportation System | Xu W.,Sun Yat Sen University | And 4 more authors.
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2011

Pollutant emissions in the street canyon with and without signals for pedestrians crossing were calculated by coupling traffic micro-simulation software with a vehicle emission model. With the simulation result as the emission source input, the flow and concentration field of the three-dimensional street canyon with the wind direction perpendicular to the street were modeled based on a k-ε model and the species transport equation. The result showed that the k-ε model and species transport equation can describe the pollutant dispersion in the three-dimensional street canyon well when the wind direction was perpendicular to the street. Two significant flow patterns can be discovered, corner eddies at the ends of the street canyon and a canyon vortex in the middle part of street canyon. The closer to the middle of street canyon, the angle between canyon vortex and the ground was nearer to 90°. The pollutant concentrations of windward and leeward side in the middle of the street canyon with signals for pedestrians crossing were 2.5 times and 2.7 times higher than the canyon without signals for pedestrians crossing. The pollutant concentration of the windward side was 18.88 mg·m-3, which was 0.89 times higher than the second National Standard. Source

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